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Record W2023559757 · doi:10.1364/oe.23.006264

Surface plasmon polaritons at linearly graded semiconductor interfaces

2015· article· en· W2023559757 on OpenAlexafffund
D. Blažek, Michael Čada, Jaromír Pištora

Bibliographic record

VenueOptics Express · 2015
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaGrantová Agentura České RepublikyEuropean Commission
KeywordsSurface plasmon polaritonSurface plasmonSemiconductorPlasmonDispersion (optics)Materials sciencePolaritonDispersion relationOpticsPermittivityGroup velocityCondensed matter physicsDielectricPhysicsOptoelectronics

Abstract

fetched live from OpenAlex

New results are reported on investigation of dispersion curves for surface plasmon polaritons (SPPs) at an inhomogenously doped semiconductor/dielectric interface whereby the dielectric is represented by the same undoped semiconductor. The doped semiconductor is described by its frequency-dependent permittivity that varies with the depth. It is shown that a transition layer (TL) with a linear change in carrier concentration supports one branch dispersion curve regardless of the TL thickness. The obtained dispersion curves reach a maximum at a finite frequency depending on the TL thickness, and subsequently asymptotically approach the zero frequency in the shortwave limit. Therefore two surface plasmon modes are supported at a given frequency: a long-wave mode with a positive group velocity and a short-wave mode with a negative group velocity. A condition of a zero group velocity can be satisfied by tuning the TL layer. It is shown that the conventional dispersion relation for SPPs at a TL with a zero thickness is an asymptotic solution, and the convergence of real dispersion curves is point-wise instead of an expected uniform convergence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.266
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2015
Admission routes2
Has abstractyes

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